Search Results (1,271)

This paper presents a mathematical modeling and advanced control strategy for the beer fermentation process, which is characterized by nonlinear biochemical kinetics and time-dependent dynamics. A biokinetic model was developed to describe the relationship between yeast growth, sugar consumption, and ethanol formation. The system was represented as a cascade of several continuous stirred-tank reactors (CSTRs), and experimental data confirmed a fermentation cycle of approximately 10 days. During this period, biomass concentration reached 6.8 g/L and ethanol levels exceeded 42 mmol/L. Substrate concentration (S) declined from 120 to 5 g/L, demonstrating effective conversion. The model was linearized around an operating point and reformulated into a 12-state-space system with input variables: temperature (set at 20–22 °C) and pH (maintained within 4.2–4.5). These inputs were controlled using fuzzy logic control (FLC) and model predictive control (MPC). Simulation results indicated that the FLC reduced temperature deviation to ±0.3 °C and minimized pH fluctuation below ±0.05. The MPC strategy improved substrate consumption efficiency by 8.5% and decreased fermentation time by 12 h under optimized input profiles. The combined FLC–MPC scheme demonstrated superior robustness, smooth trajectory tracking, and adaptability to biological variability compared to traditional methods. The developed framework supports intelligent brewery automation and provides a scalable foundation for further integration of digital fermentation technologies. Full article

Backround and Objectives: Basketball performance is shaped by repeated high-intensity actions interspersed with brief recovery. Conventional continuous or strictly incremental testing may not fully capture short active-recovery dynamics relevant to stop-and-go sports. Material and Methods: This study applied a VT₂-referenced progressive–intermittent treadmill protocol and focused on 60-s active-recovery kinetics to describe effort tolerance in an applied basketball setting. Basketball players from Mureș County completed anthropometry (24 h pre-test, fasted) and a single laboratory visit. Pre-test training and diet were standardized for 48 h (submaximal training; predominantly carbohydrate intake). CPET was performed in 3-min stages (6.5 km·h⁻¹ start; +0.7 km·h⁻¹ per stage) and stopped at RER = 1.00 and/or blood lactate = 4.0 mmol·L⁻¹ (operational VT2). After 3 min active recovery, participants completed six 60-s high-speed bouts separated by 60-s active recovery intervals (AR1–AR6), with intensities prescribed at 120–180% of VT2-derived speed, followed by an 8-min active recovery. For each AR interval, linear regression over 0–60 s yielded slopes for VO₂, VO₂/HR, VCO₂, V̇E, VE/VO₂, VE/VCO₂, and PetCO₂. Results: VT₁ was determined at 2.29 m·s⁻¹ (VO₂ 32 mL·min⁻¹·kg⁻¹) and VT2 at 3.07 m·s⁻¹ (VO₂ 42 mL·min⁻¹·kg⁻¹). Maximal intermittent speed was 5.33 m·s⁻¹ (VO₂ 45.5 mL·min⁻¹·kg⁻¹; RER 1.06; PetCO₂ 38 mmHg). VO₂ differed across successive bouts (p = 0.0001), while PetCO₂ showed a small downward drift across repetitions. Peak indices (max speed, VE/VCO₂max, PetCO₂max, VEmax) were associated with phase-specific recovery slopes across early, mid, and late recovery periods (false discovery rate–adjusted correlations). Lactate decreased over 8 min, but lactate change rates were not associated with peak indices. Conclusions: The VT₂-referenced progressive–intermittent protocol appears feasible in basketball players and provides phase-dependent recovery information that complements conventional peak CPET outcomes, with potential relevance for applied team settings. Full article

Thermal-like features in hadron production are observed in small systems such as proton–proton interactions, where conventional kinetic equilibration on sub-fm/c time scales is challenging to justify. One proposed explanation is that quantum entanglement in the incoming hadron wave functions, together with coarse-graining over unobserved degrees of freedom, can generate an entropy-like signal without requiring extensive final-state rescattering. We test whether a final-state Shannon entropy extracted from the charged-particle multiplicity distributions measured by ALICE at $\sqrt{s}=0.9$–8 TeV can be reproduced by an initial-state entanglement entropy computed from leading-order proton PDFs. In a low-x approximation where the reduced density matrix of the probed region is taken to be maximally mixed in an effective parton-number basis, the entanglement entropy reduces to $S_{EE}\simeq \ln N$, where N is obtained by integrating PDFs over an x-range mapped from the ALICE midrapidity acceptance. We include gluon and sea-quark contributions and apply correction factors accounting for the charged fraction and the limited set of measured degrees of freedom. Within the stated assumptions and PDF uncertainties, the initial- and final-state entropy become numerically compatible toward low x, supporting the interpretation that initial-state quantum entanglement can contribute to the apparent thermal-like behavior in small collision systems. Full article

Background and Objectives: Procalcitonin (PCT) is widely used to support the diagnosis of bacterial infection and sepsis, yet clinically relevant elevations also occur in multiple non-infectious conditions. This systematic review aimed to synthesize human evidence on non-infectious causes of elevated PCT and to summarize proposed pathophysiological mechanisms, with the goal of supporting context-based interpretation in clinical practice. Materials and Methods: A systematic search of PubMed/MEDLINE, Embase, Web of Science, and Scopus was performed from inception to 31 July 2025. Human studies published in English reporting quantitative PCT values in non-infectious contexts were eligible (observational studies, clinical trials, and case series with ≥5 patients). Results: Seventy-six unique studies were included. Evidence was organized across systemic inflammatory responses, cardiovascular pathology, nephrological disorders and renal replacement therapy, pulmonary diseases, gastrointestinal and hepatopancreatic diseases, autoimmune and rheumatologic conditions, neurologic and ophthalmologic conditions, onco-hematologic disorders, surgery, traumatology and transplanted patients. Across conditions, non-infectious PCT elevations were variable and frequently overlapped with ranges reported in bacterial infection, particularly in settings characterized by severe sterile inflammation and tissue injury (e.g., major surgery, trauma, shock, pancreatitis, and burns), as well as in selected malignancies with tumor-associated PCT production. Conclusions: Elevated PCT is not synonymous with bacterial infection. Interpretation should emphasize clinical context, timing, and serial trends rather than isolated thresholds, especially in high-acuity settings with strong non-infectious inflammatory stimuli. Standardized reporting of assays and sampling time points and condition-specific kinetic data are needed to refine diagnostic and stewardship algorithms. Full article

Time-resolved (TR) resonance Raman (RR) spectroscopy with continuous-wave excitation is a fundamental technique that has contributed substantially to the understanding of the structure and dynamics of retinal proteins. However, the underlying principles were developed about fifty years ago for instrumentation that is hardly in use anymore. Thus, the adaptation of the technique to the current state-of-the-art equipment is needed to satisfy the increasing demand for the spectroscopic characterization of novel retinal proteins. In this work, we focus on pump–probe TR RR experiments with a confocal spectrometer using a rotating cell. We define the parameters ensuring fresh-sample condition and the photochemical innocence of the probe beam as a prerequisite for studying retinal proteins that undergo a cyclic photoinduced reaction sequence. For the measurements of intermediate states and reaction kinetics, pump–probe experiments are required in which the two laser beams hit the flowing sample with a defined but variable delay time. An appropriate set-up for such two-beam experiments with a confocal spectrometer is proposed and tested in TR experiments of bacteriorhodopsin. The comparison with the results obtained with classical slit spectrometers using a 90-degree scattering illustrates the advantages and disadvantages of the confocal arrangement. It is shown that modern confocal spectrometers substantially decrease the spectra acquisition time but require a more demanding optical set-up. Furthermore, the extent of photoconversion by the pump beam is lower than for the 90-degree-scattering arrangement, which reduces the accuracy of kinetic measurements. Full article

Background/Objectives: To investigate and develop a non-invasive parametric radiomics model derived from dynamic contrast-enhanced MRI (DCE-MRI) time-intensity curve (TIC) kinetics for predicting breast cancer molecular subtypes (HR+/HER2−, HER2+ and triple-negative breast cancer). Methods: This multicenter retrospective study enrolled 935 female patients with histologically confirmed breast cancer who underwent pretreatment breast DCE-MRI from August 2017 to July 2022. Based on the wash-in rate (WIR) and the area under the TIC, the original multiphase DCE-MRI images were converted into two types of parametric images. Radiomics features were extracted from TIC-WIR and TIC-Area images and analyzed using low variance filtering, the elimination of highly correlated features, and the least absolute shrinkage and selection operator regression. The categorical boosting algorithm was employed to develop multiclass prediction models for breast cancer molecular subtyping. A TIC-Combined model was further established by integrating the calibrated probability outputs of the TIC-WIR and TIC-Area models using a decision-level fusion strategy. The discrimination, calibration, and interpretability of the models were evaluated in the study datasets. Results: The TIC-Combined model achieved superior predictive performance in both the internal validation set (micro-average AUC: 0.79, macro-average AUC: 0.77) and the external validation set (micro-average AUC: 0.77, macro-average AUC: 0.75). For subtype-specific classification by the TIC-Combined model, the highest one-vs-rest AUCs were 0.81 for triple-negative breast cancer in the internal validation set and 0.76 for HER2+ breast cancer in the external validation set. The TIC-Combined model also showed good calibration and high interpretability which ensured reliable predictions and provided clear insights into feature importance. Conclusions: Interpretable parametric radiomics from TIC-derived parametric maps links kinetic features to molecular phenotypes, enabling accurate and non-invasive classification of breast cancer molecular subtypes. Full article

Climate change and water pollution are the global focus to address the mitigation measures that will improve water quality and wastewater management. The recent increase in dye pollution from the manufacturing sector, particularly the textile industries, has increased the demand for advanced wastewater treatment technologies that are sustainable and affordable. The abundant, renewable lignocellulosic fiber-based adsorbents have emerged as a promising alternative for removing a wide range of heavy metals and dyes. This review highlights in detail various sources of fibers, their physicochemical compositions, and different modification techniques that improve their selectivity and adsorption capacity, particularly for dye removal. The complementary impacts of the presence of the inherent functional groups, specific surface charges, and the primary adsorption mechanisms that can significantly enhance dye selectivity have been well addressed. While the modified fibers demonstrated the promising removal efficiency of above 90% at the laboratory scale, challenges remain in terms of their adsorption kinetics, regeneration efficiency, and long-term stability for large-scale industrial settings. Hence, future studies should focus on enhancing fiber properties for sustainable industrial applications, high-performance, and multifunctionality through a promising hybrid modification technique that will bridge the gap into large industrial implementation. Full article

Post-cholecystectomy non-alcoholic fatty liver disease (NAFLD), now encompassed within metabolic dysfunction-associated steatotic liver disease (MASLD), is increasingly linked to persistent disruption of bile acid kinetics and gut–liver axis signaling after gallbladder removal. Continuous bile delivery to the intestine reshapes the bile acid pool, perturbs FXR–FGF19/TGR5 pathways, remodels gut microbiota, and compromises epithelial barrier integrity, collectively promoting portal endotoxemia, chronic hepatic inflammation, and fibrogenic remodeling. Hydrogel-based biomaterials offer a mechanistically aligned therapeutic platform for this setting because they enable localized, sustained, and stimuli-responsive interventions at intestinal or hepatic sites. Functional hydrogels can sequester excess bile acids, protect and deliver probiotics/prebiotics/postbiotics, reinforce mucosal barrier function, and provide controlled release of anti-inflammatory or antifibrotic agents with reduced systemic exposure. In this review, we map emerging hydrogel strategies relevant to post-cholecystectomy NAFLD across four pathogenic nodes, bile acid dysregulation, dysbiosis, inflammation, and fibrosis, and highlight design principles (polymer chemistry, charge/hydrophobicity balance, mucoadhesion, and pH/redox/enzyme responsiveness) that enable targeted modulation of the gut–liver axis. Finally, we identify key translational gaps, including the lack of post-cholecystectomy-specific experimental models and standardized outcome measures integrating bile acid profiling, microbiome readouts, and hepatic histology. Hydrogel technologies represent a promising route toward localized and multimodal therapy in metabolic liver disease, warranting focused preclinical validation and clinical development. Full article

Clinical trajectories following Trypanosoma cruzi infection are heterogeneous, and the determinants of post-treatment parasitological dynamics and cardiac progression remain incompletely characterized, particularly in TcI-predominant regions. This study assessed, in both the acute phase and the indeterminate chronic form, the association between TcI infection and molecular clearance kinetics, cardiac progression, and the prognostic value of early molecular response. An ambispective cohort in Colombia included patients with acute or indeterminate chronic infection followed between 2000 and 2023. Sustained clearance was defined as two consecutive negative quantitative polymerase chain reaction results obtained at separate visits. Time-to-event analyses were conducted using Kaplan–Meier curves and Cox proportional hazards models. TcI infection was consistently associated with delayed molecular clearance in both clinical presentations. Although long-term clearance was achieved in most patients, TcI infection was independently associated with a higher risk of cardiac progression. In contrast, quantitative polymerase chain reaction negativity at 12 months was associated with reduced subsequent progression risk, indicating that sustained molecular response is a clinically meaningful prognostic marker. Collectively, these findings support the incorporation of early molecular monitoring into risk-stratified follow-up strategies in TcI-predominant settings and reinforce the need for phase-specific clinical management approaches. Full article

In recent decades, layered perovskite-like oxides have been intensively investigated as prominent photocatalysts for water splitting as a method of hydrogen production. In many previous papers, it was shown that deposition of platinum on an oxide sample dramatically increases photocatalytic activity. Nevertheless, little research was conducted to reveal the localisation of platinum in layered oxides; either it is located on the surface or in the interlayer space. In the present work, an attempt to answer this question is made. An HCa₂Nb₃O₁₀ layered perovskite-like oxide was modified with platinum by photoreduction of H₂PtCl₆ and then was intercalated with n-alkylamines (R = Me, Bu, Oc). Moreover, another set of samples were prepared by intercalating the amines first into HCa₂Nb₃O₁₀, followed by Pt deposition. Besides conventional methods for sample characterisation, we measured the kinetics of Pt dissolution during aqua regia etching of the samples, hoping that the rate of platinum dissolution would provide some information about its localisation. It was shown that in HCa₂Nb₃O₁₀ modified with platinum, less than 20% of the platinum is located on the surface, and that in the case of HCa₂Nb₃O₁₀ intercalated with amines, an even smaller amount of platinum attaches to the surface. Moreover, Pt in HCa₂Nb₃O₁₀ intercalated with amines was found to be significantly more stable against aqua regia treatment than in HCa₂Nb₃O₁₀ decorated with platinum directly. Full article

DNAzymes are catalytically active single-stranded DNAs that fold into metal-ion-assisted architectures to mediate diverse reactions. Addressing the performance gap in biological settings, we establish a novel conceptual framework based on a continuous iteration workflow of selection, enhancement, and application. This paradigm integrates selection constraints, molecular engineering, and clinical context into a unified cycle. We summarize the evolution of SELEX toward application-driven selection incorporating functional/environmental constraints, deep-sequencing-enabled high-throughput activity readouts, droplet compartmentalization and structure- and computation-guided design. We further consolidate engineering strategies to improve stability, kinetics and controllability, including 2′-sugar modifications and XNA substitution, backbone and nucleobase functionalization, arm and secondary-structure engineering for switchable or split architectures and multivalent organization on nanocarriers or nucleic acid scaffolds to enhance local concentration, protection and targeted delivery. Finally, we survey applications in ultrasensitive biosensing and portable diagnostics, activatable and multimodal in vivo imaging, and therapies for cancer, inflammatory diseases and airway disorders, and outline translational priorities: data-driven design, next-generation delivery, standardized safety/PK-PD evaluation and scalable manufacturing, ultimately for clinical and point-of-care deployment. Full article

Thermoplastic carbon fiber-reinforced polymer (CFRP) composites possess the intrinsic capability to heal delamination and matrix cracks via thermal re-melting. However, under impact loading, they are prone to severe fiber fracture, which significantly compromises their repairability. To address this, this study introduced polytetrafluoroethylene (PTFE) films as pre-set interlaminar defects within continuous carbon fiber-reinforced polyamide 6 (CF/PA6) thermoplastic cross-ply laminates. Low-velocity impact tests were conducted at varying energy levels to comparatively investigate the impact response and damage mechanisms of the CFRPs with and without embedded defects. Experimental results indicate that the embedded interlaminar defects triggered a transition in the failure mode of the CFRP from brittle fracture to progressive damage behavior. Compared to the baseline laminates, the specimens with embedded defects maintained higher flexural stiffness under low-energy impact. Furthermore, they effectively reduced the extent of fiber breakage by dissipating impact kinetic energy through extensive delamination, interlaminar frictional sliding, and plastic micro-deformation. These findings verify the feasibility of achieving macroscopic pseudo-ductility through interlaminar microstructural tailoring. This research provides an experimental basis and methodological support for the pseudo-ductile design of thermoplastic composites. Full article

The cement industry is a major source of anthropogenic CO₂ emissions due to its energy-intensive production process and calcination of limestone. Producing one ton of cement emits approximately one ton of CO₂, and cement accounts for about 5% to 8% of global CO₂ emissions. In this context, cement-less one-part (“just-add-water”) ambient-cured geopolymer concrete (GPC) has gained attention due to its environmental friendliness and practicality for large-scale cast-in-situ construction. However, field adoption remains limited, mainly due to the scarcity of data on mechanical properties and durability, as well as the lack of widely accepted standards and specifications. This paper is part of the larger research on tensile performance of anchors embedded in GPC. It is well understood that the tensile performance of anchors installed in concrete substrate is largely influenced by their effective embedment depth and the substrate’s mechanical properties, particularly the fracture energy and modulus of elasticity. Therefore, prior to the investigation of the tensile performance of anchors in GPC, it is crucial to understand the mechanical behaviour of the GPC substrate itself. This study examined key parameters that influence the compressive strength of one-part ambient-cured slag/fly ash-based GPC. The alkali content, slag content, water-to-solid (W/S) ratio, and aggregate content were investigated. Additionally, various mechanical properties such as uniaxial tensile strength, splitting tensile strength, elastic modulus, and fracture energy of the hardened GPC are presented. The test results revealed that higher slag and activator content enhanced compressive strength, whereas a higher aggregate content reduced the strength. The strength gain was also attributed to higher alkali content, lower W/S ratio, and increased binder content; however, excessive alkali and an overly low W/S ratio caused rapid setting due to accelerated reaction kinetics. The 7-day compressive strength ranged from 62% to 78% of the 28-day strength, while there was no notable strength gain after 28 days of curing. The developed GPC attained compressive strengths of over 40 MPa at 28 days and 50 MPa at 56 days. The uniaxial tensile strength test demonstrated a ratio of 0.87 relative to splitting tensile strength. The findings also indicated that the aggregate conditions and curing regimes (whether using as-is aggregates with moisture curing or oven-dried aggregates with sealed curing) had no meaningful effect on the mean compressive strength of GPC and its reproducibility. Full article

Background/Objectives: Human milk is a complex biological fluid containing not only macro- and micronutrients but also diverse bioactive molecules, including extracellular RNAs. Although RNA has been detected in milk for decades, only a subset of RNA species has been characterized in detail, and abundant families such as tRNA-, yRNA-, and rRNA-derived fragments remain underexplored. This study aimed to define the composition, fragmentation patterns, stability, and exploratory functional activity of these highly abundant RNAs in human milk. Methods: We performed small RNA sequencing on skim milk samples and analyzed the resulting profiles in comparison with publicly available milk and biofluid datasets. RNA stability assays, Northern blotting, and RT-qPCR were conducted to validate RNA abundance and degradation kinetics. Extracellular vesicles (EVs) and non-vesicular fractions were analyzed to determine the subcellular distribution of RNA species. Exploratory functional assays using synthetic RNA fragments were carried out to assess their ability to modulate cellular responses in vitro. Results: Human milk was found to be highly enriched in small RNA fragments derived from tRNA, yRNA, and rRNA, dominated by a limited set of discrete sequences. These profiles were highly reproducible across independent datasets and distinct biofluids. Orthologal validation assays confirmed their abundance and stability, with RNA levels exceeding those of serum by over two orders of magnitude. Full-length transcripts were enriched in EVs, whereas shorter fragments predominated in the non-vesicular fraction. Synthetic milk-derived exRNAs showed detectable pro-survival activity under stress conditions in vitro. Conclusions: This study reveals that human milk carries a limited set of highly abundant stable sRNA molecules, primarily derived from tRNAs, yRNAs, and rRNAs. These findings provide new insights into the RNA cargo of human milk and offer preliminary evidence that selected sRNA fragments can modulate cellular stress responses in in vitro models. Full article

This research examines the risk factors that influence injury severity in individual motorcycle accidents, utilising a dataset of 5253 incidents. Five machine learning algorithms—multinomial logistic regression, classification trees, random forests, XGBoost, and neural networks—were used to classify the results into three groups: Death (13.48%), Injury (80.14%), and No injury (6.38%). In all models, passenger presence was the most important predictor of injury. Motorcycle accidents involving passengers do not always have more serious consequences for several overlapping reasons. On the one hand, a motorcycle with a passenger has a significantly higher mass, which increases the braking distance and kinetic energy at the moment of collision, hindering quick defensive manoeuvres, cornering, and reactions to sudden hazards. Often, the rider also refrains from sudden movements to prevent the passenger from losing their balance. In the case of single-rider motorcycle accidents on roadways, approximately 5% of those involved with a passenger were fatalities, while approximately 48% were uninjured; in the case of those without a passenger, no one was uninjured. It follows from the above that the presence of a passenger increases the rider’s sense of responsibility. Other factors that significantly increased risk were single-lane carriageways, vehicle overturning, contaminated road surfaces, and collisions with complex objects, e.g., like trees. The multinomial logistic regression model had an overall accuracy of 69.2% on the test set. The Recurrent Neural Network achieved the best overall accuracy of 79.56%. Balanced accuracy, as the average between sensitivity and specificity of the RNN model for the “death” class was 68.15%, for the “injury” class—72.6%, and for the “no injury” class—96.61%. The Area Under the ROC Curve of the Recurrent Neural Networks model for “no injury” was 0.97, indicating it was very good at distinguishing between this class and the other classes. Even though it was easy to tell which cases did not involve injuries, it was still hard to tell the difference between fatal and non-fatal injuries in all models. The results support interventions tailored to specific situations, such as improved road lighting and speed control in rural areas, as well as helmet enforcement and safety measures at intersections in cities. Full article